Open Access
ARTICLE
Moazam Ali, Susmit Bagchi*
Intelligent Automation & Soft Computing, Vol.24, No.4, 2018, DOI:10.31209/2018.100000043
Abstract Due to the rapid advancements and developments in wide area networks and
powerful computational resources, the load balancing mechanisms in distributed
systems have gained pervasive applications covering wired as well as mobile
distributed systems. In large-scale distributed systems, sharing of distributed
resources is required for enhancing overall resource utilization. This paper
presents a comprehensive study and detailed comparative analysis of different
load balancing algorithms employing fuzzy logic and mobile agents. We have
proposed a hybrid architecture for integrated load balancing and monitoring in
distributed computing systems employing fuzzy logic and autonomous mobile
agents. Furthermore, we have proposed a smooth and… More >
Open Access
ARTICLE
Win-Chin Lina, Chin-Chia Wua, Kejian Yub, Yong-Han Zhuanga, Shang-Chia Liuc
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 671-681, 2018, DOI:10.1080/10798587.2017.1302711
Abstract Most research studies on scheduling problems assume that a job visits certain machines only one time.
However, this assumption is invalid in some real-life situations. For example, a job may be processed
by the same machine more than once in semiconductor wafer manufacturing or in a printed circuit
board manufacturing machine. Such a setting is known as the “re-entrant flowshop”. On the other
hand, the importance of learning effect present in many practical situations such as machine shop, in
different branches of industry and for a variety of corporate activities, in shortening life cycles, and in
an increasing diversity of… More >
Open Access
ARTICLE
Young Hun Songa, Suk Leea, Kyoung Nam Hab, Kyung Chang Leec
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 683-691, 2018, DOI:10.1080/10798587.2017.1302712
Abstract Recently, FlexRay was developed to replace the controller area network (CAN) protocol in the chassis
network systems to provide high-speed data transmission as well as hardware redundancy for safety.
However, FlexRay network design is more complicated than with CAN protocol, which has been an
in-vehicle network (IVN) standard for car manufacturers for decades, because the FlexRay has many
parameters such as the base cycle or slot lengths. To simplify the FlexRay network design and assist
vehicle network designers in configuring a FlexRay network, this paper presents an automatic field
bus exchange format (FIBEX) generation method for migration from the CAN… More >
Open Access
ARTICLE
Serkan Ballıa, Mustafa Tukerb
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 693-699, 2018, DOI:10.1080/10798587.2017.1306968
Abstract Heterogeneous networks are environments where networks having different topologies and
technologies can be connected. In an environment including more than one heterogeneous access
network, selection of a bad network may lead to emergence of negative results such as high cost and
poor service experience for the users. Ensuring the use of the most effective access network for the
personal needs of individuals is a complex decision-making process. In the present study, a multicriteria decision-making system employing fuzzy logic was developed to evaluate and select network
service providers in Turkey. Fuzzy logic was used for the criteria containing uncertain and unclear… More >
Open Access
ARTICLE
U. Kanimozhi, D. Manjula
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 701-709, 2018, DOI:10.1080/10798587.2017.1307626
Abstract We are witnessing the era of big data computing where computing the resources is becoming the main
bottleneck to deal with those large datasets. In the case of high-dimensional data where each view of
data is of high dimensionality, feature selection is necessary for further improving the clustering and
classification results. In this paper, we propose a new feature selection method, Incremental Filtering
Feature Selection (IF2S) algorithm, and a new clustering algorithm, Temporal Interval based Fuzzy
Minimal Clustering (TIFMC) algorithm that employs the Fuzzy Rough Set for selecting optimal subset
of features and for effective grouping of large volumes of… More >
Open Access
ARTICLE
Geetha N., Sankar A.
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 711-719, 2018, DOI:10.1080/10798587.2017.1309003
Abstract The routing protocol for an ad hoc network should be efficient in utilizing the available resources to
prolong the network lifetime. A Multi Criterion Fuzzy based Energy Efficient Routing Protocol (MCFEER)
for Ad hoc Networks selects the path on constraints like bandwidth, battery life, hop count and buffer
occupancy. In the route discovery phase, fuzzy system is applied for optimal route selection by
destination node leading to successful data transmission. Multiple stable paths are preserved in route
cache for usage during the route maintenance phase. The results are competitive when compared with
Power aware Energy Efficient Routing (PEER) protocol using… More >
Open Access
ARTICLE
Masoumeh Zareapoor, Jie Yang
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 721-727, 2018, DOI:10.1080/10798587.2017.1321228
Abstract The design of an efficient credit card fraud detection technique is, however, particularly challenging,
due to the most striking characteristics which are; imbalancedness and non-stationary environment
of the data. These issues in credit card datasets limit the machine learning algorithm to show a
good performance in detecting the frauds. The research in the area of credit card fraud detection
focused on detection the fraudulent transaction by analysis of normality and abnormality concepts.
Balancing strategy which is designed in this paper can facilitate classification and retrieval problems
in this domain. In this paper, we consider the classification problem in supervised learning… More >
Open Access
ARTICLE
Li-Hong Juanga, Ming-Ni Wub, Feng-Mao Tsoub
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 739-745, 2018, DOI:10.1080/10798587.2017.1327549
Abstract Kinect(+openCV); Dynamic
portrait segmentation;
Skeletal tracking; Edge
transparent processing;
Video interactive More >
Open Access
ARTICLE
M. Umaa,c, T. Sheelab
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 747-757, 2018, DOI:10.1080/10798587.2017.1332804
Abstract Brain-Computer Interfaces (BCI) use Electroencephalography (EEG) signals recorded from the brain
scalp, which enable a communication between the human and the outside world. The present study
helps the patients who are people locked-in to manage their needs such as accessing of web url’s,
sending/receiving sms to/from mobile device, personalized music player, personalized movie player,
wheelchair control and home appliances control. In the proposed system, the user needs are designed
as a button in the form of a matrix, in which the main panel of rows and columns button is flashed in 3
sec intervals. Subjects were asked to choose the… More >
Open Access
ARTICLE
Julius Beneoluchi Odilia, Mohd Nizam Mohmad Kahara, A. Noraziaha,b, M. Zarinac, Riaz Ul Haqa
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 759-769, 2018, DOI:10.1080/10798587.2017.1334370
Abstract This paper carries out a performance analysis of major Nature-inspired Algorithms in solving the
benchmark symmetric and asymmetric Traveling Salesman’s Problems (TSP). Knowledge of the
workings of the TSP is very useful in strategic management as it provides useful guidance to planners.
After critical assessments of the performances of eleven algorithms consisting of two heuristics
(Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s
Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and
seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African
Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and… More >
Open Access
ARTICLE
Xiaofeng Liu, Siqi An, Dongxu Zhang
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 771-775, 2018, DOI:10.1080/10798587.2017.1337667
Abstract This paper discusses the problem of dynamic output consensus for heterogeneous multi-agent
systems (MAS) with fixed topologies. All the agents possess unique linear dynamics, and only the
output information of each agent is delivered throughout the communication digraphs. A series of
conditions and protocols are set for reaching the consensus. With the proper feedback controllers, the
output consensus of the overall system is guaranteed. An application illustrates the theorems. More >
Open Access
ARTICLE
Akram M. Radwana,b, Zehra Cataltepea,c
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 777-783, 2018, DOI:10.1080/10798587.2017.1337673
Abstract This paper proposes to apply machine learning techniques to predict students’ performance on two
real-world educational data-sets. The first data-set is used to predict the response of students with
autism while they learn a specific task, whereas the second one is used to predict students’ failure at a
secondary school. The two data-sets suffer from two major problems that can negatively impact the
ability of classification models to predict the correct label; class imbalance and class noise. A series
of experiments have been carried out to improve the quality of training data, and hence improve
prediction results. In this paper,… More >
Open Access
ARTICLE
Juan C. Quiroza, Amit Banerjeeb, Sergiu M. Dascaluc, Sian Lun Laua
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 785-793, 2018, DOI:10.1080/10798587.2017.1342400
Abstract We use the public Human Activity Recognition Using Smartphones (HARUS) data-set to investigate
and identify the most informative features for determining the physical activity performed by a user
based on smartphone accelerometer and gyroscope data. The HARUS data-set includes 561 time
domain and frequency domain features extracted from sensor readings collected from a smartphone
carried by 30 users while performing specific activities. We compare the performance of a decision
tree, support vector machines, Naive Bayes, multilayer perceptron, and bagging. We report the various
classification performances of these algorithms for subject independent cases. Our results show that
bagging and the multilayer… More >
Open Access
ARTICLE
M. A. Kamela, M. A. Abidob, Moustafa Elshafeic
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 795-805, 2018, DOI:10.1080/10798587.2017.1342414
Abstract Directional Steering System (DSS) has been established for well drilling in the oilfield in order to
accomplish high reservoir productivity and to improve accessibility of oil reservoirs in complex
locations. In this paper, a novel feedback linearization controller to cancel the nonlinear dynamics of a
DSS is proposed. The proposed controller design problem is formulated as an optimization problem for
optimal settings of the controller feedback gains. Gravitational Search Algorithm (GSA) is developed to
search for optimal settings of the proposed controller. The objective function considered is to minimize
the tracking error and drilling efforts. In this study, the DSS… More >
Open Access
ARTICLE
Yiğit Kültür, Mehmet Ufuk Çağlayan
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 807-817, 2018, DOI:10.1080/10798587.2017.1342415
Abstract Because credit card fraud costs the banking sector billions of dollars every year, decreasing the losses
incurred from credit card fraud is an important driver for the sector and end-users. In this paper, we
focus on analyzing cardholder spending behavior and propose a novel cardholder behavior model
for detecting credit card fraud. The model is called the Cardholder Behavior Model (CBM). Two focus
points are proposed and evaluated for CBMs. The first focus point is building the behavior model
using single-card transactions versus multi-card transactions. As the second focus point, we introduce
holiday seasons as spending periods that are different… More >
Open Access
ARTICLE
Jing Jiaa, Tinghuai Mab, Fan Xinga, William Faraha, Donghai Guana,c
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 819-827, 2018, DOI:10.1080/10798587.2017.1355656
Abstract Ego networks consist of a user and his/her friends and depending on the number of friends a user
has, makes them cumbersome to deal with. Social Networks allow users to manually categorize their
“circle of friends”, but in today’s social networks due to the unlimited number of friends a user has, it is
imperative to find a suitable method to automatically administrate these friends. Manually categorizing
friends means that the user has to regularly check and update his circle of friends whenever the friends
list grows. This may be time consuming for users and the results may not be accurate… More >
Open Access
ARTICLE
Jinseok Woo, János Botzheim, Naoyuki Kubota
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 829-841, 2018, DOI:10.1080/10798587.2017.1364919
Abstract This paper introduces the integrated system of a smart-device-based cognitive robot partner called
iPhonoid-C. Interaction with a robot partner requires many elements, including verbal communication,
nonverbal communication, and embodiment as well. A robot partner should be able to understand
human sentences, as well as nonverbal information such as human gestures. In the proposed system,
the robot has an emotional model connecting the input information from the human with the robot’s
behavior. Since emotions are involved in human natural communication, and emotion has a significant
impact on humans’ actions, it is important to develop an emotional model for the robot partner… More >
Open Access
ARTICLE
H. Anandakumara, K. Umamaheswarib
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 843-849, 2018, DOI:10.1080/10798587.2017.1364931
Abstract Cognitive radio systems necessitate the incorporation of cooperative spectrum sensing among cognitive
users to increase the reliability of detection. We have found that cooperative spectrum sensing is not
only advantageous, but is also essential to avoid interference with any primary users. Interference by
licensed users becomes a chief concern and issue, which affects primary as well as secondary users
leading to restrictions in spectrum sensing in cognitive radios. When the number of cognitive users
increases, the overheads of the systems, which are meant to report the sensing results to the common
receiver, which becomes massive. When the spectrum, which is… More >
Open Access
ARTICLE
M. Carmel Sobia1, A. Abudhahir2
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 869-881, 2018, DOI:10.31209/2018.100000014
Abstract In this paper, an efficient facial expression recognition system using ANFIS-MHS
(Adaptive Network-based Fuzzy Inference System with Mosquito Host-Seeking)
has been proposed. The features were extracted using MLDA (Modified Linear
Discriminant Analysis) and then the optimized parameters are computed by
using mGSO (modified Glow-worm Swarm Optimization).The proposed system
recognizes the facial expressions using ANFIS-MHS. The experimental results
demonstrate that the proposed technique is performed better than existing
classification schemes like HAKELM (Hybridization of Adaptive Kernel based
Extreme Learning Machine), Support Vector Machine (SVM) and Principal
Component Analysis (PCA). The proposed approach is implemented in MATLAB. More >
Open Access
ARTICLE
Dong Huanga,b, Yong Baib, Jingcheng Liuc, Hongtao Chend, Jinghua Lind, Jingjing Wud
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 883-889, 2018, DOI:10.1080/10798587.2017.1327634
Abstract With limited homogeneous and heterogeneous resources in a cloud computing system, it is not feasible
to successively expand network infrastructure to adequately support the rapid growth in the cloud
service. In this paper, an approach for optimal transmission of hierarchical network for heterogeneous
service in Cloud Scenarios was presented. Initially, the theoretical optimal transmission model of a
common network was transformed into the hierarchical network with the upper and lower optimization
transmission model. Furthermore, the computation simplification and engineering transformation
were presented for an approximation method at the low cost of computational complexity. In the final
section, the average delay… More >
Open Access
ARTICLE
Mahiye Uluyagmur Ozturka, Ayse Rodopman Armanb, Gresa Carkaxhiu Bulutc, Onur Tugce Poyraz Findikb, Sultan Seval Yilmazd, Herdem Aslan Gencb, M. Yanki Yazgane,f, Umut Tekera, Zehra Cataltepea
Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 891-905, 2018, DOI:10.31209/2018.100000058
Abstract Emotion recognition behavior and performance may vary between people with major
neurodevelopmental disorders such as Autism Spectrum Disorder (ASD), Attention Deficit
Hyperactivity Disorder (ADHD) and control groups. It is crucial to identify these differences
for early diagnosis and individual treatment purposes. This study represents a
methodology by using statistical data analysis and machine learning to provide help to
psychiatrists and therapists on the diagnosis and individualized treatment of participants
with ASD and ADHD. In this paper we propose an emotion recognition experiment
environment and collect eye tracker fixation data together with the application log data
(APL). In order to detect… More >
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